Does observability affect prosociality?

The observation of behaviour is a key theoretical parameter underlying a number of models of prosociality. However, the empirical findings showing the effect of observability on prosociality are mixed. In this meta-analysis, we explore the boundary conditions that may account for this variability, by exploring key theoretical and methodological moderators of this link. We identified 117 papers yielding 134 study level effects (Total N = 788, 164) and found a small but statistically significant, positive association between observability and prosociality (r = .141, 95% CI = .106, .175). Moderator analysis showed that observability produced stronger effects on prosociality (1) in the presence of passive observers (i.e., people whose role was to only observe participants) vs perceptions of being watched, (2) when participants decisions were consequential (vs non-consequential), (3) when the studies were performed in the laboratory (as opposed to in the field/online), (4) when studies used repeated measures (instead of single games) and (5) when studies involved social dilemmas (instead of bargaining games). These effects show the conditions under which observability effects on prosociality will be maximally observed. We describe the theoretical and practical significance of 14 these results

Dispositional free riders do not free ride on punishment

Strong reciprocity explains prosocial cooperation by the presence of individuals who incur costs to help those who helped them (‘strong positive reciprocity’) and to punish those who wronged them (‘strong negative reciprocity’). Theories of social preferences predict that in contrast to ‘strong reciprocators’, self-regarding people cooperate and punish only if there are sufficient future benefits. Here, we test this prediction in a two-stage design. First, participants are classified according to their disposition towards strong positive reciprocity as either dispositional conditional cooperators (DCC) or dispositional free riders (DFR). Participants then play a one-shot public goods game, either with or without punishment. As expected, DFR cooperate only when punishment is possible, whereas DCC cooperate without punishment. Surprisingly, dispositions towards strong positive reciprocity are unrelated to strong negative reciprocity: punishment by DCC and DFR is practically identical. The ‘burden of cooperation’ is thus carried by a larger set of individuals than previously assumed

Machine Learning Approach for Prescriptive Plant Breeding

We explored the capability of fusing high dimensional phenotypic trait (phenomic) data with a machine learning (ML) approach to provide plant breeders the tools to do both in-season seed yield (SY) prediction and prescriptive cultivar development for targeted agro-management practices (e.g., row spacing and seeding density). We phenotyped 32 SoyNAM parent genotypes in two independent studies each with contrasting agro-management treatments (two row spacing, three seeding densities). Phenotypic trait data (canopy temperature, chlorophyll content, hyperspectral reflectance, leaf area index, and light interception) were generated using an array of sensors at three growth stages during the growing season and seed yield (SY) determined by machine harvest. Random forest (RF) was used to train models for SY prediction using phenotypic traits (predictor variables) to identify the optimal temporal combination of variables to maximize accuracy and resource allocation. RF models were trained using data from both experiments and individually for each agro-management treatment. We report the most important traits agnostic of agro-management practices. Several predictor variables showed conditional importance dependent on the agro-management system. We assembled predictive models to enable in-season SY prediction, enabling the development of a framework to integrate phenomics information with powerful ML for prediction enabled prescriptive plant breeding

Subcellular Localization of Hexokinases I and II Directs the Metabolic Fate of Glucose

The first step in glucose metabolism is conversion of glucose to glucose 6-phosphate (G-6-P) by hexokinases (HKs), a family with 4 isoforms. The two most common isoforms, HKI and HKII, have overlapping tissue expression, but different subcellular distributions, with HKI associated mainly with mitochondria and HKII associated with both mitochondrial and cytoplasmic compartments. Here we tested the hypothesis that these different subcellular distributions are associated with different metabolic roles, with mitochondrially-bound HK's channeling G-6-P towards glycolysis (catabolic use), and cytoplasmic HKII regulating glycogen formation (anabolic use).To study subcellular translocation of HKs in living cells, we expressed HKI and HKII linked to YFP in CHO cells. We concomitantly recorded the effects on glucose handling using the FRET based intracellular glucose biosensor, FLIPglu-600 mM, and glycogen formation using a glycogen-associated protein, PTG, tagged with GFP. Our results demonstrate that HKI remains strongly bound to mitochondria, whereas HKII translocates between mitochondria and the cytosol in response to glucose, G-6-P and Akt, but not ATP. Metabolic measurements suggest that HKI exclusively promotes glycolysis, whereas HKII has a more complex role, promoting glycolysis when bound to mitochondria and glycogen synthesis when located in the cytosol. Glycogen breakdown upon glucose removal leads to HKII inhibition and dissociation from mitochondria, probably mediated by increases in glycogen-derived G-6-P.These findings show that the catabolic versus anabolic fate of glucose is dynamically regulated by extracellular glucose via signaling molecules such as intracellular glucose, G-6-P and Akt through regulation and subcellular translocation of HKII. In contrast, HKI, which activity and regulation is much less sensitive to these factors, is mainly committed to glycolysis. This may be an important mechanism by which HK's allow cells to adapt to changing metabolic conditions to maintain energy balance and avoid injury

Prevalence and onset of comorbidities in the CDKL5 disorder differ from Rett syndrome

Background: Initially described as an early onset seizure variant of Rett syndrome, the CDKL5 disorder is now considered as an independent entity. However, little is currently known about the full spectrum of comorbidities that affect these patients and available literature is limited to small case series. This study aimed to use a large international sample to examine the prevalence in this disorder of comorbidities of epilepsy, gastrointestinal problems including feeding difficulties, sleep and respiratory problems and scoliosis and their relationships with age and genotype. Prevalence and onset were also compared with those occurring in Rett syndrome. Methods: Data for the CDKL5 disorder and Rett syndrome were sourced from the International CDKL5 Disorder Database (ICDD), InterRett and the Australian Rett syndrome Database (ARSD). Logistic regression (multivariate and univariate) was used to analyse the relationships between age group, mutation type and the prevalence of various comorbidities. Binary longitudinal data from the ARSD and the equivalent cross-sectional data from ICDD were examined using generalized linear models with generalized estimating equations. The Kaplan-Meier method was used to estimate the failure function for the two disorders and the log-rank test was used to compare the two functions. Results: The likelihood of experiencing epilepsy, GI problems, respiratory problems, and scoliosis in the CDKL5 disorder increased with age and males were more vulnerable to respiratory and sleep problems than females. We did not identify any statistically significant relationships between mutation group and prevalence of comorbidities. Epilepsy, GI problems and sleep abnormalities were more common in the CDKL5 disorder than in Rett syndrome whilst scoliosis and respiratory problems were less prevalent. Conclusion: This study captured a much clearer picture of the CDKL5 disorder than previously possible using the largest sample available to date. There were differences in the presentation of clinical features occurring in the CDKL5 disorder and in Rett syndrome, reinforcing the concept that CDKL5 is an independent disorder with its own distinctive characteristics

Using co-authorship networks to map and analyse global Neglected Tropical Disease research with an affiliation to Germany

Neglected tropical disease research has changed considerably in recent decades, and the German government is committed to addressing its past neglect of NTD research. Our aim was to use an innovative social network analysis of bibliometric data to map neglected tropical disease research networks that are inside of and affiliated with Germany, thereby enabling data-driven health policy decision-making. We created and analysed co-author networks from publications in the SCOPUS database, with a focus on five diseases. We found that Germany's share of global publication output for NTDs is approximately half that of other medical research fields. Furthermore, we identified institutions with prominent NTD research within Germany and strong research collaborations between German institutions and partners abroad, mostly in other high-income countries. This allowed an assessment of strong collaborations for further development, e.g., for research capacity strengthening in low-income-countries, but also for identifying missed opportunities for collaboration within the network. Through co-authorship network analysis of individual researcher networks, we identified strong performers by using classic bibliometric parameters, and we identified academic talent by social network analysis parameters on an individual level

The CDKL5 disorder is an independent clinical entity associated with early-onset encephalopathy

The clinical understanding of the CDKL5 disorder remains limited, with most information being derived from small patient groups seen at individual centres. This study uses a large international data collection to describe the clinical profile of the CDKL5 disorder and compare with Rett syndrome (RTT). Information on individuals with cyclin-dependent kinase-like 5 (CDKL5) mutations (n=86) and females with MECP2 mutations (n=920) was sourced from the InterRett database. Available photographs of CDKL5 patients were examined for dysmorphic features. The proportion of CDKL5 patients meeting the recent Neul criteria for atypical RTT was determined. Logistic regression and time-to-event analyses were used to compare the occurrence of Rett-like features in those with MECP2 and CDKL5 mutations. Most individuals with CDKL5 mutations had severe developmental delay from birth, seizure onset before the age of 3 months and similar non-dysmorphic features. Less than one-quarter met the criteria for early-onset seizure variant RTT. Seizures and sleep disturbances were more common than in those with MECP2 mutations whereas features of regression and spinal curvature were less common. The CDKL5 disorder presents with a distinct clinical profile and a subtle facial, limb and hand phenotype that may assist in differentiation from other early-onset encephalopathies. Although mutations in the CDKL5 gene have been described in association with the early-onset variant of RTT, in our study the majority did not meet these criteria. Therefore, the CDKL5 disorder should be considered separate to RTT, rather than another variant

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente